With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective This study aimed to investigate the efficacy of modified endoscopic autologous cartilage eustachian tube pharyngeal orifice tuboplasty(MEACETT)in patients with patulous eustachian tube(PET).Meth-ods A retrospective analysis was conducted on the clinical data of 27 patients(30 ears)diagnosed with PET who underwent MEACETT.Autologous cartilage was used through the incision at the posterior end of the inferior turbi-nate and filled into the lateral wall of the pharyngeal orifice of the eustachian tube.Without affecting the movement function of the eustachian tube during swallowing,the collapse of the pharyngeal orifice was fully filled.Before and after the surgery,the visual analogue scale(VAS),the eustachian tube dysfunction questionnaire-7(ETDQ-7)and hospital anxiety and depression scale(HADS)was used for assessment to evaluate the surgical efficacy.Results There was no significant difference in depression scores before and after surgery(P＞0.05).However,postopera-tive anxiety scores,ETDQ-7 scores,and VAS scores were significantly lower than preoperative scores(P＜0.05).Among the 27 patients,9 showed significant symptom relief,13 exhibited partial relief,and 5 had no significant change compared to preoperative symptoms.The overall response rate of the treatment(significant relief and partial relief)was 81.48％(22/27).All surgeries were successfully performed.Except for secretory otitis media occurring in 2 cases,no major complications were observed.Conclusion MEACETT demonstrates significant symptom relief in PET patients,with high surgical safety and low complication rates,making it worthy of clinical promotion.

Objective To evaluate the diagnostic efficacy of the R value in tubomanometry(TMM)for the di-agnosis of patulous eustachian tube(PET).Methods The clinical data of 58 patients with PET and 65 controls were retrospectively analyzed.TMM was performed on both groups under nasopharyngeal pressures of 30,40,and 50 mbar respectively.The diagnostic efficacy of the R value for PET was evaluated through receiver operating char-acteristic(ROC)curves.Results In the control group,the average R values under nasopharyngeal pressures of 30,40,and 50 mbar were 0.86±0.50,0.76±0.41,and 0.68±0.34 respectively.In contrast,the corresponding R values in the PET group were significantly lower,which were 0.56±0.38,0.50±0.36,and 0.46±0.38 respec-tively.According to the ROC curve analysis,the areas under the curve(AUC)at these pressures were 0.62,0.74,and 0.74 respectively.The specificity and sensitivity of the R value under nasopharyngeal pressures of 30,40,and 50 mbar were 76.90％and 54.30％,74.60％and 68.10％,86.90％and 54.30％,respectively.Under pressures of 30,40,and 50 mbar,the incidence rates of R＞1 in the control group and the PET group were 29.23％(38/130)and 12.77％(12/94)(x2=8.69,P=0.003),20.00％(26/130)and 6.38％(6/94)(x2=7.20,P=0.007),10.00％(13/130)and 3.19％(3/94)(x2=2.87,P=0.09)respectively.Conclusion Although the low R value in TMM reflects the presence of PET to some extent,it does not provide adequate sensitivity and specificity to serve as an independent diagnostic criterion for PET.

The conventional identification and prediction for failures of medical equipment mainly depend on experience and knowledge of manager for equipment,which are not able to be quantified and have lower efficiency. Therefore,it is obvious that the prediction for the failure of medical equipment is not accurate. With the technical development of computer and machine learning,the conventional identification and prediction that depend on experiences can deal with characteristics of failures through machine learning method to improve efficiency,which are hopeful in filling the gap of discipline about the identification and prediction for failures of medical equipment. This article summarized the application situation of machine learning in identifying and predicting failures of the medical equipment and the similarly electric equipment at home and abroad. Based on the key technique of identification and prediction,this article proposed suggestion about corresponding design architecture. According to the characteristics of the failure of medical equipment,this article summarized a series of information about algorithms of various machine learning in scene and accurate rate of identification and prediction,so as to provide references for relevant research of this field.

Objective To compare the biomechanical characteristics of novel retrograde intramedullary nail,common femoral retrograde intramedullary nail,and medial femoral condyle locking plate for treating distal femur type A fractures by finite element analysis,and study the advantages of retrograde intramedullary nail on medial femoral condyle.Methods A novel retrograde intramedullary nail on medial femur condyle was designed.CT scan was performed on lower limb bones of a male volunteer,and a three-dimensional(3D)model of the femur was established.The model was then segmented to create models of distal femur type A2 and A3 fractures.The 3D models of internal fixator were established.The small and standard retrograde intramedullary nail on medial femoral condyle,common femoral retrograde intramedullary nail,locking plate on medial femoral condyle were used for internal fixation on A2 type fracture.A3 type fracture was fixed with one of the above internal fixators combined with lateral condylar plate respectively.The 600 N axial load and 4 N·m torsional load were applied to the models.The displacement and stress of femurs,the displacement and stress of internal fixators,the micro-momentum between the internal fixator and the bone,the relative displacement of the two fracture broken ends were observed in each group.Results Among the A2 and A3 type fractures under axial loads,the correponding standard group and corresponding standard combined group had the smallest peak displacement and peak stress of internal fixation.Among the A2 and A3 type fractures under torsional loads,the correponding standard group and corresponding standard combined group had the smallest peak displacement of the femur and internal fixation.The relative displacement of the two broken ends in the standard combined group was the smallest.Conclusions Compared with femoral medial condylar locking plate and common retrograde intramedullary nail,this novel retrograde intramedullary nail on medial femur condyle has a mechanical advantage of reducing stress concentration and reducing the risk of internal fixation failure,and it can be used alone for distal femur type A2 fracture,or in combination with the lateral condylar plate to fix distal femur type A3 fracture.

Objective To compare the biomechanical characteristics of novel retrograde intramedullary nail,common femoral retrograde intramedullary nail,and medial femoral condyle locking plate for treating distal femur type A fractures by finite element analysis,and study the advantages of retrograde intramedullary nail on medial femoral condyle.Methods A novel retrograde intramedullary nail on medial femur condyle was designed.CT scan was performed on lower limb bones of a male volunteer,and a three-dimensional(3D)model of the femur was established.The model was then segmented to create models of distal femur type A2 and A3 fractures.The 3D models of internal fixator were established.The small and standard retrograde intramedullary nail on medial femoral condyle,common femoral retrograde intramedullary nail,locking plate on medial femoral condyle were used for internal fixation on A2 type fracture.A3 type fracture was fixed with one of the above internal fixators combined with lateral condylar plate respectively.The 600 N axial load and 4 N·m torsional load were applied to the models.The displacement and stress of femurs,the displacement and stress of internal fixators,the micro-momentum between the internal fixator and the bone,the relative displacement of the two fracture broken ends were observed in each group.Results Among the A2 and A3 type fractures under axial loads,the correponding standard group and corresponding standard combined group had the smallest peak displacement and peak stress of internal fixation.Among the A2 and A3 type fractures under torsional loads,the correponding standard group and corresponding standard combined group had the smallest peak displacement of the femur and internal fixation.The relative displacement of the two broken ends in the standard combined group was the smallest.Conclusions Compared with femoral medial condylar locking plate and common retrograde intramedullary nail,this novel retrograde intramedullary nail on medial femur condyle has a mechanical advantage of reducing stress concentration and reducing the risk of internal fixation failure,and it can be used alone for distal femur type A2 fracture,or in combination with the lateral condylar plate to fix distal femur type A3 fracture.

BACKGROUND:Finite element analysis is an advanced computer-based engineering technique that uses mathematical approximations to simulate the human body.This method accurately reflects the biomechanical characteristics within the knee,providing a powerful tool for understanding knee disease pathogenesis,optimizing surgical protocols,and developing new implant materials.OBJECTIVE:To review the establishment of finite element modelling of the knee joint and its application in the study of knee joint diseases,and look forward to the future development trend.METHODS:The first author searched the PubMed and EI databases in April 2024 by applying a computer with English search terms"finite element analysis,FEA,knee joint,finite element model,knee biomechanics,knee osteoarthritis,knee prosthesis,knee ligaments,meniscus"and searched CNKI and WanFang databases with Chinese search terms"finite element analysis,finite element model,knee joint,biomechanics,osteoarthritis,computational model,knee prosthesis,knee ligament,meniscus."Finally,75 papers were included in the analysis.RESULTS AND CONCLUSION:(1)Finite element analysis method uses medical imaging data to obtain a three-dimensional human model,simplifies the complex human joint structure into finite and interconnected units,and visually displays the internal stress distribution of the knee joint by applying external loads to the model.(2)The researchers deeply study the internal stress and strain distribution of the knee joint under different working conditions by means of finite element analysis,revealing the overloading of the articular cartilage and the decrease of load in some areas when the balance of the internal load distribution of the knee joint is changed,and that such long-term abnormal stresses cause deformation,wear and tear,and eventual loss of cartilage,which is crucial for understanding how biomechanical factors cause degenerative changes of the knee joint.(3)The effect of physical therapy methods such as Tai Chi and gait adjustment in patients with osteoarthritis of the knee joint was evaluated by finite element analysis,and the results showed that these treatments reduced the overloading of the cartilage,which provided a scientific theoretical basis for clinical treatment.(4)Clinicians are able to optimize surgical treatment strategies by performing three-dimensional reconstruction,data measurement,and simulation of surgery before surgery through finite element analysis.Furthermore,the mechanical characteristics of different prostheses can be simulated to improve the shape,material,and fixation of the prostheses,reduce patient complications,and improve patient outcomes.(5)The combination of artificial intelligence and finite element analysis makes the construction of finite element models more accurate and easy to operate,greatly contributing to the efficiency of clinicians'medical practice and patient outcomes.(6)Finite element analysis is only a digital simulation,which is still somewhat different from the real physical state.

The conventional identification and prediction for failures of medical equipment mainly depend on experience and knowledge of manager for equipment,which are not able to be quantified and have lower efficiency. Therefore,it is obvious that the prediction for the failure of medical equipment is not accurate. With the technical development of computer and machine learning,the conventional identification and prediction that depend on experiences can deal with characteristics of failures through machine learning method to improve efficiency,which are hopeful in filling the gap of discipline about the identification and prediction for failures of medical equipment. This article summarized the application situation of machine learning in identifying and predicting failures of the medical equipment and the similarly electric equipment at home and abroad. Based on the key technique of identification and prediction,this article proposed suggestion about corresponding design architecture. According to the characteristics of the failure of medical equipment,this article summarized a series of information about algorithms of various machine learning in scene and accurate rate of identification and prediction,so as to provide references for relevant research of this field.

To investigate the role of the DPP4-nestin axis in liver fibrosis induced by alveolar cyst infection,a murine model was established using C57BL/6 mice via hepatic portal vein injection.Liver histopathological changes were assessed using HE staining,while immunohistochemistry and immunofluorescence were employed to evaluate the expression levels of nestin and DPP4 in infected mouse livers.In vitro,J S1 cell line was stimulated with recombinant DPP4 protein to es-tablish a cellular model,and qPCR,Western blot,and shRNA lentivirus interference techniques were utilized to examine the involvement of the DPP4-nestin axis in hepatic stellate cell activation.The findings demonstrated that compared to the Sham group,liver tissue structure disruption and collagen deposition were evident along with significantly increased expressions of nestin and DPP4(P＜0.050 0),which colocalized with nesin and α-SMA.Furthermore,stimulation with recombi-nant DPP4 protein significantly enhanced JS1 cell activation(P＜0.050 0)as well as upregulated nestin expression(P＜0.050 0)when compared to control group cells.Notably,shRNA lentivirus-mediated inhibition of nestin expression effectively suppressed the activating effects exerted by re-combinant DPP4 protein on JS1 cells(P＜0.050 0).Collectively,these results highlight the crucial regulatory role played by the DPP4-nestin axis in hepatic stellate cell activation triggered by alveo-lar infection;thus,targeting this axis may represent a novel therapeutic strategy for treating alveo-lar infection-induced liver fibrosis.

Objective This study aimed to investigate the efficacy of modified endoscopic autologous cartilage eustachian tube pharyngeal orifice tuboplasty(MEACETT)in patients with patulous eustachian tube(PET).Meth-ods A retrospective analysis was conducted on the clinical data of 27 patients(30 ears)diagnosed with PET who underwent MEACETT.Autologous cartilage was used through the incision at the posterior end of the inferior turbi-nate and filled into the lateral wall of the pharyngeal orifice of the eustachian tube.Without affecting the movement function of the eustachian tube during swallowing,the collapse of the pharyngeal orifice was fully filled.Before and after the surgery,the visual analogue scale(VAS),the eustachian tube dysfunction questionnaire-7(ETDQ-7)and hospital anxiety and depression scale(HADS)was used for assessment to evaluate the surgical efficacy.Results There was no significant difference in depression scores before and after surgery(P＞0.05).However,postopera-tive anxiety scores,ETDQ-7 scores,and VAS scores were significantly lower than preoperative scores(P＜0.05).Among the 27 patients,9 showed significant symptom relief,13 exhibited partial relief,and 5 had no significant change compared to preoperative symptoms.The overall response rate of the treatment(significant relief and partial relief)was 81.48％(22/27).All surgeries were successfully performed.Except for secretory otitis media occurring in 2 cases,no major complications were observed.Conclusion MEACETT demonstrates significant symptom relief in PET patients,with high surgical safety and low complication rates,making it worthy of clinical promotion.